Adapting rebuilding of encoded data slices in a dispersed storage network

ABSTRACT

A method for execution by a storage unit of a dispersed storage network includes updating a rebuilding task list based on detecting at least one storage error associated with storage of encoded data slices in a set of storage units that includes the storage unit. An encoded data slice is rebuilt based on the rebuilding task list and an affinity with the encoded data slice. The rebuilding task list is again updated based on detecting execution of at least one task of the rebuilding task list. The rebuilding task list is further updated based on detecting expiration of an execution time frame between sequential tasks of the rebuilding task list.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility patent application claims priority pursuant to35 U.S.C. § 120 as a continuation-in-part of U.S. Utility applicationSer. No. 15/006,845, entitled “PRIORITIZING REBUILDING OF ENCODED DATASLICES”, filed Jan. 26, 2016, which claims priority pursuant to 35U.S.C. § 119(e) to U.S. Provisional Application No. 62/141,034, entitled“REBUILDING ENCODED DATA SLICES ASSOCIATED WITH STORAGE ERRORS,” filedMar. 31, 2015, both of which are hereby incorporated herein by referencein their entirety and made part of the present U.S. Utility patentapplication for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention; and

FIG. 10 is a logic diagram of an example of a method of adaptingrebuilding of encoded data slices.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

In various embodiments, each of the storage units operates as adistributed storage and task (DST) execution unit, and is operable tostore dispersed error encoded data and/or to execute, in a distributedmanner, one or more tasks on data. The tasks may be a simple function(e.g., a mathematical function, a logic function, an identify function,a find function, a search engine function, a replace function, etc.), acomplex function (e.g., compression, human and/or computer languagetranslation, text-to-voice conversion, voice-to-text conversion, etc.),multiple simple and/or complex functions, one or more algorithms, one ormore applications, etc. Hereafter, a storage unit may be interchangeablyreferred to as a dispersed storage and task (DST) execution unit and aset of storage units may be interchangeably referred to as a set of DSTexecution units.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each managing unit 18 and the integrity processing unit 20 maybe separate computing devices, may be a common computing device, and/ormay be integrated into one or more of the computing devices 12-16 and/orinto one or more of the storage units 36. In various embodiments,computing devices 12-16 can include user devices and/or can be utilizedby a requesting entity generating access requests, which can includerequests to read or write data to storage units in the DSN.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN memory 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the 10 deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as 10 ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. Here, the computing device stores data object40, which can include a file (e.g., text, video, audio, etc.), or otherdata arrangement. The dispersed storage error encoding parametersinclude an encoding function (e.g., information dispersal algorithm(IDA), Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides dataobject 40 into a plurality of fixed sized data segments (e.g., 1 throughY of a fixed size in range of Kilo-bytes to Tera-bytes or more). Thenumber of data segments created is dependent of the size of the data andthe data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 80 is shown inFIG. 6. As shown, the slice name (SN) 80 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of another embodiment of a dispersedstorage network (DSN) that includes a plurality of distributed storageand task (DST) integrity processing units 1-D, the network 24 of FIG. 1,and a set of DST execution (EX) units 1-n. Each DST integrity processingunit can be implemented utilizing the integrity processing unit 20 ofFIG. 1. Each DST execution unit includes a rebuilding module 508 and amemory 88. The rebuilding module 508 can be implemented utilizing thecomputing core 26 of FIG. 2. The memory 88 can be implemented byutilizing the main memory 54 of FIG. 2. Each DST execution unit can beimplemented utilizing the storage unit 36 of FIG. 1. The DSN functionsto adapt rebuilding of encoded data slices associated with one or morestorage errors.

Storage units can utilize the reception of listing requests to determinethe current global state of recently scanned namespace ranges as anintegral function of “co-operative rebuild scanning”. However, there isother useful information communicated to other storage units duringrebuilding which can also be leveraged. For example, rebuild modules ina DSN memory can also utilize current and accurate informationpertaining to if and/or when a source becomes unhealthy, how unhealthy agiven source is compared to other sources (i.e., how many slices is itmissing), who should be responsible for rebuilding a given unhealthysource, if and/or when the responsible entity is derelict or deficientin their duties to rebuild, if and/or when an unhealthy source becomeshealthy, and/or which namespace ranges have gone the longest withoutbeing checked for unhealthy sources.

Cooperative rebuild scanning which utilizes the reception of in-boundlisting requests sent by rebuild modules can be utilized, but moreinformation is available to leverage. For example, in a scheme involvingrebuild mailboxes (either shared or disparate queues of unhealthysources to be rebuilt), storage units that receive read requests fromrebuild modules for slices belonging to unhealthy sources may presumethat another rebuild module is in the process of rebuilding that sourceand therefore that it can be removed from its own mailbox (since anotherrebuild module has processed it). Likewise, a determination may be madethat a certain rebuild module is being derelict in its rebuild functionsif it fails to make listing, or read requests over a certain period oftime, or is issuing them at too low (or suspiciously high) of a rate.This can trigger other rebuild modules to take over that rebuildmodule's task queue (or otherwise determined responsibilities).Deterministic or time-based functions such as a Distributed AgreementProtocol (DAP) or similar scheme can also be utilized to determine whois responsible for rebuilding a given unhealthy source. How unhealthy agiven source is compared to other sources can be determined by listing,and for maximum utility in prioritizing rebuild tasks, it can becommunicated to the rebuild module(s) responsible for its restoration.If and when a source becomes unhealthy can be determined in response todrive failure, and/or rebuilt entries may be inserted directly bycomputing devices which fail to fully write all their slices (or writethem to temporary locations under a foster slice/target width/trimmedwrite scenario). With all of this information available to rebuildmodules, more intelligent and responsive actions can be taken to recoverthe most unhealthy data as expeditiously as possible. Since normallyreads are issued to only a read-threshold number of storage units ratherthan a full width, to maximize dissemination of the information, rebuildmodules can purposely issue reads to a full width, or issue checkrequests to the storage units that don't get reads, for example, inorder to signal their progress being made towards the rebuilding of asource to other rebuild modules.

In an example of operation of the adapting of the rebuilding, the DSclient module 34 (e.g., of at least one of a DST integrity processingunit and/or of any DST execution unit) updates a rebuilding task list510 based on detecting one or more storage errors associated withstorage of encoded data slices in the set of DST execution units. Forexample, the DS client module 34 issues list slice requests, receiveslist slice responses as slice integrity information, detects a storageerror, updates the rebuilding task list five and 10 to include anidentifier of a slice name associated with the storage error, andpublishes (e.g., sends), via the network 24, the updated rebuilding tasklist 514 to each of the storage units.

Having received the updated rebuilding task list 514, the DST executionunit 1 can interpret the rebuilding task list to identify an encodeddata slice requiring rebuilding, where the encoded data slice isassociated with the DST execution unit 1. For example, the rebuildingmodule 508 of the DST execution unit 1 compares slice names of a localslice list to slice names of the rebuilding task list. Having identifiedthe encoded data slice requiring rebuilding, the DST execution unit 1can facilitate the rebuilding of the encoded data slice to produce arebuilt encoded data slice 512 for storage in the memory 88 of the DSTexecution unit 1. For example, the DST execution unit 1 issues, via thenetwork 24, read slice requests to other DST execution units, recovers adata segment from encoded data slices of received read slice responses,and re-encodes the recovered data segment to produce the rebuilt encodeddata slice 512 for storage in the memory 88.

The DST execution unit 2 can interpret the read slice requests from theDST execution unit 1 (e.g., and perhaps others) to update a local copyof the rebuilding task list. The updating can include removing one ormore rebuilding tasks associated with encoded data slices of a set ofencoded data slices that includes the encoded data slice that wasrebuilt by the DST execution unit 1.

The DST execution unit 3 can interpret received list slice requests toupdate its local copy of the rebuilding task list with regards to theother encoded data slice not being associated with the list slicerequests, for example, when a time frame between the receiving of listslice requests for the other encoded data slices is greater than a timethreshold level (e.g., detect an unfavorable slice error scanning rate).The updating can further include adding additional rebuilding tasks toabate the slow scanning of slice errors. The DST execution unit 3 canperform the additional rebuilding task. For example, the rebuildingmodule of the DST execution unit 3 issues list slice requests to otherDST execution units, receives list slice responses as slice integrityinformation, identifies slice errors, and/or updates its local copy ofthe rebuilding task list by storing the updated rebuilding task list 514in the memory 88 of the DST execution unit 3.

In various embodiments, a processing system of a storage unit includesat least one processor and a memory that stores operationalinstructions, that when executed by the at least one processor cause theprocessing system to update a rebuilding task list based on detecting atleast one storage error associated with storage of encoded data slicesin a set of storage units that includes the storage unit. An encodeddata slice is rebuilt based on the rebuilding task list and an affinitywith the encoded data slice. The rebuilding task list is again updatedbased on detecting execution of at least one task of the rebuilding tasklist. The rebuilding task list is further updated based on detectingexpiration of an execution time frame between sequential tasks of therebuilding task list.

In various embodiments, the encoded data slice is associated with atleast one data segment, and wherein the data segment was dispersedstorage error encoded to produce a set of encoded data slices thatincludes the encoded data slice for storage in the set of storage units.In various embodiments, a scan for encoded data slice errors isperformed and the at least one storage error is detected as a result ofperforming the scan. In various embodiments, updating the rebuildingtask list includes modifying the rebuilding task list to include atleast one task that addresses the at least one storage error. In variousembodiments, updating the rebuilding task list includes generating anupdated rebuilding task list. The updated rebuilding task list istransmitted to the set of storage units. In various embodiments,updating the rebuilding task list includes generating an updatedrebuilding task list. An update notification is transmitted to the setof storage units in response to the generation of the updated rebuildingtask list, and at least one of the set of storage units accesses theupdated rebuilding task list in response to receiving the updatenotification.

In various embodiments, rebuilding the encoded data slice includesinterpreting the rebuilding task list to identify a plurality of tasksassociated with a rebuilding module of the storage unit. A plurality ofpriority levels corresponding to the plurality of tasks is generated,and the plurality of tasks are executed in accordance with the pluralityof priority levels to rebuild the encoded data slice. In variousembodiments, the plurality of priority levels are generated based on acalculated severity estimate and/or a calculated rebuild time. Invarious embodiments, the encoded data slice is rebuilt in response to aplurality of tasks of the rebuilding task list indicating that no otherrebuilding module is designated to rebuild the encoded data slice withina rebuilding time frame.

In various embodiments, updating the rebuilding task list based ondetecting the execution of the at least one task includes locating theleast one task in a plurality of tasks of the rebuilding task list andremoving the at least one task from the rebuilding task list to producean updated rebuilding task list. In various embodiments, updating therebuilding task list based on detecting the expiration of the executiontime frame includes re-prioritizing tasks of the rebuilding task list inresponse to determining that the execution time frame has expired from afirst task of the sequential tasks.

FIG. 10 is a flowchart illustrating an example of adapting rebuilding ofencoded data slices. In particular, a method is presented for use inassociation with one or more functions and features described inconjunction with FIGS. 1-9, for execution by a dispersed storage andtask (DST) integrity processing unit that includes a processor, arebuilding module or other processing system of a DST execution unitthat includes a processor, and/or via another processing system of adispersed storage network that includes at least one processor andmemory that stores instruction that configure the processor orprocessors to perform the steps described below.

The method includes step 520 where a processing system (e.g., ofdispersed storage and task (DST) integrity processing unit and/or a DSTexecution unit) updates a rebuilding task list based on detecting one ormore storage errors associated with storage of encoded data slices in aset of storage units. For example, the processing system scans for sliceerrors, detects the slice errors, modifies the rebuilding task list toinclude one or more tasks to address the detected slice errors, and/orpublishes the rebuilding task list to other entities of a dispersedstorage network (DSN) by transmitting the rebuilding task list orotherwise making the updated rebuilding task list to the other entities,for example, where the other entities receive notifications that therebuilding task list has been updated and access the updated rebuildingtask list in response.

The method continues at step 522 where the processing system rebuilds anencoded data slice based on the rebuilding task list and an affinitywith the encoded data slice. For example, the processing systeminterprets the rebuilding task includes identify tasks associated with arebuilding module; prioritizes the identified tasks based on one or moreof a severity estimate, a time to rebuild, and/or a desired rebuildingschedule; and/or executes the prioritized tasks to rebuild encoded dataslice (e.g., rebuilding encoded data slice associated with therebuilding module when no other rebuilding module is expected to rebuildthe encoded data slice within a desired rebuilding time frame).

The method continues at step 524 where the processing system updates therebuilding task list based on detecting execution of one or more tasksof the rebuilding task list. For example, the processing systeminterprets one or more received messages to identify the execution ofthe one or more tasks, locates one or more tasks of the rebuilding tasklist associated with the identified one or more tasks, removes thelocated one or more tasks of the rebuilding task list to produce anupdated rebuilding task list, and/or publishes the updated rebuildingtask list to at least some of the entities of the DSN.

The method continues at step 526 where the processing system furtherupdates the rebuilding task list based on detecting expiration of anexecution time frame between sequential tasks of the rebuilding tasklist. For example, the processing system determines that the executiontimeframe has expired from a first task of the two sequential tasks andre-prioritizes tasks of the rebuilding task list to facilitate a moretimely execution of an original task of the rebuilding (e.g., a localrebuilding module performs the original task).

In various embodiments, a non-transitory computer readable storagemedium includes at least one memory section that stores operationalinstructions that, when executed by a processing system of a dispersedstorage network (DSN) that includes a processor and a memory, causes theprocessing system to update a rebuilding task list based on detecting atleast one storage error associated with storage of encoded data slicesin a set of storage units that includes the storage unit. An encodeddata slice is rebuilt based on the rebuilding task list and an affinitywith the encoded data slice. The rebuilding task list is again updatedbased on detecting execution of at least one task of the rebuilding tasklist. The rebuilding task list is further updated based on detectingexpiration of an execution time frame between sequential tasks of therebuilding task list.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing system”, “processingmodule”, “processing circuit”, “processor”, and/or “processing unit” maybe used interchangeably, and may be a single processing device or aplurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing system, processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing system, processing module, module,processing circuit, and/or processing unit. Such a memory device may bea read-only memory, random access memory, volatile memory, non-volatilememory, static memory, dynamic memory, flash memory, cache memory,and/or any device that stores digital information. Note that if theprocessing system, processing module, module, processing circuit, and/orprocessing unit includes more than one processing device, the processingdevices may be centrally located (e.g., directly coupled together via awired and/or wireless bus structure) or may be distributedly located(e.g., cloud computing via indirect coupling via a local area networkand/or a wide area network). Further note that if the processing system,processing module, module, processing circuit, and/or processing unitimplements one or more of its functions via a state machine, analogcircuitry, digital circuitry, and/or logic circuitry, the memory and/ormemory element storing the corresponding operational instructions may beembedded within, or external to, the circuitry comprising the statemachine, analog circuitry, digital circuitry, and/or logic circuitry.Still further note that, the memory element may store, and theprocessing system, processing module, module, processing circuit, and/orprocessing unit executes, hard coded and/or operational instructionscorresponding to at least some of the steps and/or functions illustratedin one or more of the Figures. Such a memory device or memory elementcan be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by a storage unit thatincludes a processor, the method comprises: updating a rebuilding tasklist based on detecting at least one storage error associated withstorage of encoded data slices in a set of storage units that includesthe storage unit; rebuilding an encoded data slice based on therebuilding task list and an affinity with the encoded data slice;updating the rebuilding task list based on detecting execution of atleast one task of the rebuilding task list; and updating the rebuildingtask list based on detecting expiration of an execution time framebetween sequential tasks of the rebuilding task list.
 2. The method ofclaim 1, wherein the encoded data slice is associated with at least onedata segment, and wherein the data segment was dispersed storage errorencoded to produce a set of encoded data slices that includes theencoded data slice for storage in the set of storage units.
 3. Themethod of claim 1, further comprising performing a scan for encoded dataslice errors, wherein the at least one storage error is detected as aresult of performing the scan.
 4. The method of claim 1, whereinupdating the rebuilding task list includes modifying the rebuilding tasklist to include at least one task that addresses the at least onestorage error.
 5. The method of claim 1, wherein updating the rebuildingtask list includes generating an updated rebuilding task list, furthercomprising transmitting the updated rebuilding task list to the set ofstorage units.
 6. The method of claim 1, wherein updating the rebuildingtask list includes generating an updated rebuilding task list, whereinan update notification is transmitted to the set of storage units inresponse to the generation of the updated rebuilding task list, andwherein at least one of the set of storage units accesses the updatedrebuilding task list in response to receiving the update notification.7. The method of claim 1, wherein rebuilding the encoded data sliceincludes: interpreting the rebuilding task list to identify a pluralityof tasks associated with a rebuilding module of the storage unit;generating a plurality of priority levels corresponding to the pluralityof tasks; and executing the plurality of tasks in accordance with theplurality of priority levels to rebuild the encoded data slice.
 8. Themethod of claim 7, wherein the plurality of priority levels aregenerated based on at least one of: a calculated severity estimate or acalculated rebuild time.
 9. The method of claim 1, wherein the encodeddata slice is rebuilt in response to a plurality of tasks of therebuilding task list indicating that no other rebuilding module isdesignated to rebuild the encoded data slice within a rebuilding timeframe.
 10. The method of claim 1, wherein updating the rebuilding tasklist based on detecting the execution of the at least one task includes:locating the at least one task in a plurality of tasks of the rebuildingtask list; and removing the at least one task from the rebuilding tasklist to produce an updated rebuilding task list.
 11. The method of claim1, wherein updating the rebuilding task list based on detecting theexpiration of the execution time frame includes re-prioritizing tasks ofthe rebuilding task list in response to determining that the executiontime frame has expired from a first task of the sequential tasks.
 12. Aprocessing system of a storage unit comprises: at least one processor; amemory that stores operational instructions, that when executed by theat least one processor cause the processing system to: update arebuilding task list based on detecting at least one storage errorassociated with storage of encoded data slices in a set of storage unitsthat includes the storage unit; rebuild an encoded data slice based onthe rebuilding task list and an affinity with the encoded data slice;update the rebuilding task list based on detecting execution of at leastone task of the rebuilding task list; and update the rebuilding tasklist based on detecting expiration of an execution time frame betweensequential tasks of the rebuilding task list.
 13. The processing systemof claim 12, wherein the encoded data slice is associated with at leastone data segment, and wherein the data segment was dispersed storageerror encoded to produce a set of encoded data slices that includes theencoded data slice for storage in the set of storage units.
 14. Theprocessing system of claim 12, wherein the at least one storage error isdetected as a result of performing a scan for encoded data slice errors.15. The processing system of claim 12, wherein updating the rebuildingtask list includes modifying the rebuilding task list to include atleast one task that addresses the at least one storage error.
 16. Theprocessing system of claim 12, wherein updating the rebuilding task listincludes generating an updated rebuilding task list, and wherein theoperational instructions, when executed by the at least one processor,further cause the processing system to transmit the updated rebuildingtask list to the set of storage units.
 17. The processing system ofclaim 12, wherein rebuilding the encoded data slice includes:interpreting the rebuilding task list to identify a plurality of tasksassociated with a rebuilding module of the storage unit; generating aplurality of priority levels corresponding to the plurality of tasks;and executing the plurality of tasks in accordance with the plurality ofpriority levels to rebuild the encoded data slice.
 18. The processingsystem of claim 12, wherein the encoded data slice is rebuilt inresponse to a plurality of tasks of the rebuilding task list indicatingthat no other rebuilding module is designated to rebuild the encodeddata slice within a rebuilding time frame.
 19. The processing system ofclaim 12, wherein updating the rebuilding task list based on detectingthe expiration of the execution time frame includes re-prioritizingtasks of the rebuilding task list in response to determining that theexecution time frame has expired from a first task of the sequentialtasks.
 20. A computer readable storage medium comprises: at least onememory section that stores operational instructions that, when executedby a processing system of a dispersed storage network (DSN) thatincludes a processor and a memory, causes the processing system to:update a rebuilding task list based on detecting at least one storageerror associated with storage of encoded data slices in a set of storageunits; rebuild an encoded data slice based on the rebuilding task listand an affinity with the encoded data slice; update the rebuilding tasklist based on detecting execution of at least one task of the rebuildingtask list; and update the rebuilding task list based on detectingexpiration of an execution time frame between sequential tasks of therebuilding task list.